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Tag - MNIST

Over the course of many debugging sessions, I’ve compiled my experience along with the best ideas around in this handy list. I hope they would be useful to you. comments By Slav Ivanov, Entrepreneur & ML Practitioner. The network had been training fo...

This intro to ANNs will look at how we can train an algorithm to recognize images of handwritten digits. We will be using the images from the famous MNIST (Mixed National Institute of Standards and Technology) database. By Kenneth Soo, Stanford. Take...

In this recurring monthly feature, we filter recent research papers appearing on the arXiv.org preprint server for compelling subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and compute...

Automatic feature engineering using Generative Adversarial Networks Application to computer vision and synthetic financial transactions data The purpose of deep learning is to learn a representation of high dimensional and noisy data using a sequence...

A new data set for the study of sequence learning algorithms is available as of today. The data set consists of pen stroke sequences that represent handwritten digits, and was created based on the MNIST handwritten digit data set. By Dr. Edwin D. de...

At the end of this post, you’ll be able to implement a neural network to identify handwritten digits using the MNIST dataset and have a rough time idea about how to build your own neural networks. By Raksham Pandey, Vivekanand Education Society's Ins...

In this excellent tutorial video presentation below, Magnus Erik Hvass Pedersen demonstrates the basic workflow of using TensorFlow with a simple linear model. After loading the so-called MNIST data-set with images of hand-written digits, he defines...

Despite DL many successes, there are at least 4 situations where it is more of a hindrance, including low-budget problems, or when explaining models and features to general public is required. comments By Pablo Cordero, Hyperparameter. I know it’s a...